The queries in QuAC also include ellipse phenomena which make them ambiguous and under-specified, similar to those in CAsT.
 [1]} recruit a group of crowd workers to manually rewrite the QuAC queries into de-contextulized queries that include all the information necessary to understand the information needs. The resultant CANARD dataset includes manually de-contextualized queries for all QuAC's dev set and a sample of 4,873 conversation topics (34,956) from QuAC's training set.
Then, the QuAC dev set is used as a test set, as the QuAC test set is hidden, and the annotated training topics is split to train/dev with a 9:1 ratio.
